Data Engineer

Zealogics LLC
Lehi, UT, United States
19 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours

Tech stack

Airflow Amazon Web Services Amazon S3 Apache HTTP Server Microsoft Azure Cloud Computing Cloud Storage Databases Data Architecture Information Engineering Data Infrastructure Extract Transform Load (ETL)
+25 more
Data Vault Modeling Data Warehousing Document Management Systems Dimensional Modeling PostgreSQL Meta-Data Management Metadata Repositories MySQL Performance Tuning SAP (Applications) Enterprise Data Management Freeform SQL Cloud Platform System Document Metadata Sql Optimization Database Optimization Apache Spark Indexer Data Layers Data Lineage Collibra Physical Data Models Data Pipelines Legacy Systems Databricks

Job description

Job Title: Senior Data Engineer (Data Modeling & Multi-Source Integration) Experience: 5 - 8 Years Position Overview Zealogics Technologies is seeking an experienced and analytical Senior Data Engineer (5-8 years) to architect, model, and optimize the foundational data infrastructure for a brand-new strategic project. This role requires deep expertise in establishing relationships across heterogeneous data sources (SAP Core, PostgreSQL, MySQL), building comprehensive data catalogs/lineage, and fine-tuning high-performance data pipelines. Key Responsibilities

  • Data Modeling & Relationship Mapping: Architect conceptual, logical, and physical data models for a new enterprise solution. Identify, map, and resolve complex entity relationships across SAP Core, PostgreSQL, MySQL, and legacy systems.
  • Data Lineage & Cataloging: Implement enterprise data cataloging, metadata tracking, and end-to-end data lineage to ensure visibility, governance, and auditability across all data layers.
  • Performance Optimization & Tuning: Analyze execution plans, optimize complex SQL queries, fine-tune database configurations, indexing, and partitioning to ensure high throughput and minimal latency.
  • Document & Unstructured Metadata Management (Advantageous): Design and maintain robust metadata indexing mechanisms for large-scale document management systems (e.g., In-house DMS, Azure Blob Storage).
  • Pipeline Engineering: Build reliable ETL/ELT data pipelines integrating structured, semi-structured, and enterprise data repositories into a unified system.
  • Cross-Functional Collaboration: Partner with enterprise architects, product owners, and global client technical teams to translate business requirements into scalable data architectures.

Requirements

  • Experience: 5-8 years of dedicated hands-on experience in Data Engineering, Data Architecture, and Enterprise Data Modeling.
  • Data Modeling Mastery: Proven expertise in dimensional modeling, Data Vault, ER diagrams, and multi-source relationship mapping.
  • Heterogeneous Databases: Solid expertise in working with SAP Core, PostgreSQL, and MySQL.
  • Governance & Lineage: Experience with modern data cataloging and lineage tools (e.g., OpenMetadata, Apache Atlas, Microsoft Purview, Collibra, or dbt docs).
  • Performance Tuning: Expert knowledge in SQL optimization, indexing strategies, memory tuning, and query troubleshooting.
  • Cloud & Modern Data Stack: Hands-on experience with cloud ecosystems (Azure/AWS) and pipeline orchestration tools (Spark, Databricks, dbt, Airflow, etc.).
  • Strong verbal and professional communication skills to deal with architects & data engineers across globe.

Preferred / Nice-to-Have Skills

  • Proven ability to extract, index, and manage metadata for large enterprise document repositories (In-house DMS, Azure Blob Storage, S3).
  • Exposure to OCR/document metadata workflows and semi-structured cataloging.
  • Prior experience delivering high-impact solutions for global clients and internal products.

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